Summary of paper:
As mobile phones advance in functionality and capability, they are being used for more than just communication. Increasingly, these devices are being employed as instruments for introspection into habits and situations of individuals and communities. Many of the applications enabled by this new use of mobile phones rely on contextual information. The focus of this work is on one dimension of context, the transportation mode of an individual when outside. The transportation modes identified include whether an individual is stationary, walking, running, biking, or in motorized transport. The overall classification system consists of a decision tree followed by a first-order discrete Hidden Markov Model and achieves an accuracy level of 93.6% when tested
on a dataset obtained from sixteen individuals. The sensors used are GPS and acclerometer.

Biography:
Leon Stenneth is a third year PhD, CS student working under the supervision of Professor Ouri Wolfson and Professor Philip Yu. His research entails privacy aware location based services and context aware computing. Leonís most recent research project is determining transportation mode from mobile device's sensors, this motivates the reason for presenting this ACM journal entry.